The broad goal is to contribute to the understanding of how individual genomic variation contributes to disease susceptibility and response to drugs, by exploring the effects of mutations in coding regions on protein structure. The work will focus on developing a computational method to predict the functional effects of non-synonymous single nucleotide polymorphisms, using a combination of features derived from multiple sequence alignments, experimental structures when available, and comparative models otherwise. AIM1: Quantitatively identify the sequence- and structure-based features of nsSNP variants that are most informative in predicting functional effects and the best way to combine them in a predictive algorithm. AIM2: Apply and validate the method by predicting the impact of nsSNPs in human membrane transporters, a class of proteins important for determining the levels at which therapeutic drugs are effective, in collaboration with biologists in the UCSF Pharmacogenomics of Membrane Transporters (PMT) project. AIM3: Maximize the utility of the method to biologists by implementing and maintaining a webserver that provides functional predictions for human nsSNPs, bi-directionally linked to the UCSC Genome Browser. [unreadable] [unreadable]